Tangyou Huang, Zhongcheng Yu, Zhongyi Ni, Xiaoji Zhou, Xiaopeng Li
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引用次数: 0
Abstract
High sensitivity detection plays a vital role in science discoveries and technological applications. While intriguing methods utilizing collective many-body correlations and quantum entanglements have been developed in physics to enhance sensitivity, their practical implementation remains challenging due to rigorous technological requirements. Here, we propose an entirely data-driven approach that harnesses the capabilities of machine learning, to significantly augment weak-signal detection sensitivity. In an atomic force sensor, our method combines a digital replica of force-free data with anomaly detection technique, devoid of any prior knowledge about the physical system or assumptions regarding the sensing process. Our findings demonstrate a significant advancement in sensitivity, achieving an order of magnitude improvement over conventional protocols in detecting a weak force of approximately 10−25N. The resulting sensitivity reaches $$1.7(4)\times 1{0}^{-25}\,{{{{{{{\rm{N}}}}}}}}/\sqrt{{{{{{{{\rm{Hz}}}}}}}}}$$ . Our machine learning-based signal processing approach does not rely on system-specific details or processed signals, rendering it highly applicable to sensing technologies across various domains. In this study, the authors propose a generic machine-learning-assisted framework to improve the overall performance of quantum sensing application. In the context of an atomic force sensor, this entirely data-driven approach, which involves generating the digital twinning of experimental data, demonstrates an order of magnitude improvement in sensitivity compared to conventional protocols.
期刊介绍:
Communications Physics is an open access journal from Nature Research publishing high-quality research, reviews and commentary in all areas of the physical sciences. Research papers published by the journal represent significant advances bringing new insight to a specialized area of research in physics. We also aim to provide a community forum for issues of importance to all physicists, regardless of sub-discipline.
The scope of the journal covers all areas of experimental, applied, fundamental, and interdisciplinary physical sciences. Primary research published in Communications Physics includes novel experimental results, new techniques or computational methods that may influence the work of others in the sub-discipline. We also consider submissions from adjacent research fields where the central advance of the study is of interest to physicists, for example material sciences, physical chemistry and technologies.